No …. However, design them to be technically credible, scientifically defensible, and politically effective if they are adaptively designed.

Assume that public policies will fail to fully embrace temporal, spatial, perceptual, goal based failures.

incorporate an “error-provocative design” within the policy – i.e., assume that flaws are inevitable and politically-unavoidable given the interest group pressures in their design (Ackerman, 1980; Robison, 1994).

Prepare for these flaws by providing checks and balances in their implementation – at the first sign of a problem, even a “street-level bureaucrat” responsible for some policy “mode” can veto a decision; demand that some problem be inspected, audited, examined, evaluated, or revisited.

Permit input from a wide range of stakeholders & provide capacity to modify the policy or program when new information is acquired.

Can we ensure that policies succeed?

NASA manned-spaceflight missions …. since the space shuttle accidents of 1986 and 2004 (Challenger and Columbia).

FEMA has begun elements of this …. since Hurricane Katrina.

Department of Interior/Mining and Minerals Service … since the Gulf oil spill of 2010.

Nuclear Regulatory Commission … since Three Mile Island (1979).

Common denominators? Scandal, accident, tragedy, high-consequence failure. What is missing, however, is long term planning or anticipation of problems.

Examples?

Worldwide – as nation-states develop, aspirations for a better life grow, and expectations rise – policy problems are converging in 2 major ways.

Problems becoming comparable the world over – e.g., health care needed as populations age; demands for more “rights” as countries modernize; demands for more “cradle-to-grave” protection as economies become more complex.

Solutions becoming comparably constrained – less revenue + growing public demands for more of everything = policy-makers under stress (lack of trust and confidence in policy processes).

Conclusions – future challenges facing the study of public policy

In developing countries, greater demands for public participation in decisions; less tolerance for authoritarian policy-making.

In more developed countries, less trust of “experts” and an “expert state; greater movement by groups and parties toward center of the political spectrum for solutions. What is the “center”?

Less regulation, more partnership with civil society, greater devolution of policy implementation to lower- jurisdictions, more “incremental” or path dependent innovation – no more New Deals, New Frontiers, or “Wars on poverty, inflation, cancer.”

Greater demands for policy “thickening” in matters of risk; e.g., environmental protection, health and education, and consumer product safety.

Implications of these challenges

We simultaneously demand less harm and greater protection (which implies more government) but at same time we are concerned with fair allocation of benefits and risks (implying greater liberty):

Requires greater reliance on science and allowance for public participation. Can these two things be reconciled?

Myth: scientists produce and deliver information to policy-makers who then rely on them for making decisions (“loading dock” model).

Reality: as we have seen, use of science by policy-makers is complicated:

Scientists/experts may disagree with one another–a policy analysis problem. Scientists not always good at translating work into policy information. Public has vague understanding of science. Change in society partly determined by science, partly by social choices.

So … what’s the problem?

AB 32 – The CO2 emissions strategy for California

• At tip of triangle scientists and other knowledge-producers share common language and tools.

• As findings and outcomes become increasingly different, a learning process must occur for information to be translated (middle of triangle) to policy-makers and public.

• Finally, science must share the stage with ethics, politics and other “uncertain” areas of information in order to achieve policy “transformation,” including changes in behavior – i.e., citizen science.

Translating science for policy

This model was developed for NOAA to depict how climate information (i.e., “forecasts” of weather, long-term climate trends are translated and used by decision-makers.

Definition – science-society collaboration & production of policy-specific knowledge designed to solve problems (Gibbons, 1999; Jasanoff, 2004):

Mobilizes academic and pragmatic knowledge and experience to produce better solutions to environmental, health, technological problems and issues.

Grounds broad, theoretical scientific assumptions in a “place-based” setting – this is where problems must be solved!

Promotes longer-term thinking about impacts and responsibilities – including our individual responsibilities to future generations (take what we learn and apply it to our lives).

Emphasizes experimentation and two-way communication – i.e., not science as a “loading dock” but science as a circuitous, iterative learning process.

Citizen science as transformation

Example of translational science - The Regional Integrated Sciences and Assessments (RISA) program

- Team members primarily based at universities though some are based at government research facilities, non-profit organizations or private sector entities.

- Research focuses on the fisheries, water, wildfire, and agriculture sectors – work with citizen groups as well as agencies on climate-related issues (e.g., flood, drought, weather variability).

- Program also supports research into climate sensitive health issues. More recently, coastal restoration has also become an important research focus for some of the teams working with NGOs.

Public participation variously defined:

Passive vs. proactive.

Passive - acquiescence/opposition through expression of favorable or unfavorable opinion by public (e.g., polling, focus groups).

Currently done in many policy areas – ineffective in creating a sense of community or policy “ownership.”

Pro-active - active role in making decisions through legally-sanctioned, unconventional mechanisms (e.g., advisory boards or citizen-oversight bodies.

Has been attempted in many environmental and community health and development policies. Can be effective, but it requires much thought in program design!

Public participation as additional solution

Many agencies responsible for environmental, health, urban planning decisions operate under “ethos” of secrecy: Closed deliberative processes Hierarchical command and control

Many agencies lack staff with experience, training, inclination to embrace/guide broad input: Public works agencies, anti-poverty and public housing programs Hard to convince agencies that while participation may slow decision-making;

it may make decisions more durable & just.

Defining the “public” is a challenge: Should participants be those subject to economic or other impacts? Should participation be limited to elected officials or NGO leaders/activists?

Public participation barriers

Practice informed consent: In a democracy, citizens have a need to know the consequences of decisions that affect their lives. Information needed for informed consent not always provided, or made understandable.

Communicate risks effectively: know your audience and talk TO them - not at them – use non-technical language (P. Slovic; R. Kasperson, M. Rushefsky).

Acknowledge uncertainties: and acknowledge that people worry about consequences, not probabilities.

Provide a forum in which analysts, policy makers, citizens are able to identify a common idiom for debate: this gets participants to acknowledge there are alternative points of view on any issue that must be heard if debate is to move forward – a so-called “epistemic community (Haas, 1990)” (RISA is an example).

Keys to participation and policy success

Public policy began as an optimistic enterprise committed to the view that societies can “engineer” solutions to problems (e.g., Plato, Aristotle, Montesquieu).

It is also a field that has had to face the limitations of organizational democracy and unequal power (e.g., Michels and oligarchy; Weber and Comte on expertise).

The duality and complexities of science and ethics has also been a pre-occupation (e.g., Stone, Radin). We seek to reconcile both because:

We want to evaluate the efficacy of processes and outcomes. We know policies have consequences for efficiency and equity. We want to learn how to design policies to serve society’s needs more

effectively (e.g., de Mesquita, Ellis, Pal & Weaver, Levin & Shapiro).

Conclusions